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Towards a data driven healthcare system

In our last post, ‘Can Analytics Save the NHS from Collapse?’ we discussed the lack of adoption of data analytics technologies by the NHS – and reasons behind this. There’s no doubt the challenges are real, but for me, the benefits of using analytics are considerable and outweigh the cons. In this latest post, it’s those benefits I’d like to focus on.

Being informed by descriptive, diagnostic, predictive and prescriptive analytics will enable NHS managers and employees to make better decisions

Here’s how analytics can help:

1. Improvements in capacity and throughput
NHS hospitals are incredibly complex structures with interacting processes and workflows. If any of these workflows fail to meet capacity demands, bottlenecks occur which are not conducive to optimising patient outcomes or costs. The key to managing processes and capacity better is contained within the incredible amount of data generated and stored by hospitals.

There is a wealth of data both internal to the NHS and externally – either public and free or available through subscription. Consequently, patients could be better served and costs managed more efficiently by using more information, more sophisticated technologies and better statistical models to more accurately forecast demand, right down to different shift levels.

Unfortunately, there is more information than can be managed or mined and only sophisticated, structured data management and analytics systems can extract the insights that provide management and staff with what they need to plan and optimise workflows.

Between 3 to 6 percent improvements in hospital capacity and throughput can be expected from an integrated hospital-wide deployment of data & analytics, creating potentially millions of pounds in savings.

2. Projected outcomes for the NHS
Analytics can also enable the treatment of patients on time. Availability of accurate and timely management data for planning and real-time management bed occupancy will make great steps to achieve this. In addition, staff would also be managed accordingly.

3. Better integration
Integrating data analysis and sharing with other healthcare agencies will help to manage capacity, improve workflow and deliver holistic patient care. Not only that, but NHS managers will be able to create robust and detailed plans for priorities, for example, identifying areas that can be served by community resources rather than a hospital to moderate demand on hospital resources.

Being informed by descriptive, diagnostic, predictive and prescriptive analytics will enable NHS managers and employees to make better decisions, leading to an all-round, better run NHS. Well, that’s the idea. In the next of our healthcare series, we’ll be looking at analytics deployment best practice.

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